Real-Time Pump Monitoring with Prescriptive Analytics

1. A method for performing real-time pump monitoring with prescriptive analytics, the method comprising: receiving, by one or more servers, real-time sensor data from at least one sensor indicative of at least one characteristic of an operation of a pump of a pump system; updating, by the one or more servers, a first threshold value via use of machine learning to generate an updated first threshold value, the one or more servers being communicatively coupled to at least one of the at least one sensor; determining, by the one or more servers, whether a first portion of the real-time sensor data is outside of the updated first threshold value; determining a first fault information in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value; displaying, in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value, the first fault information on a graphical user interface of an administrative device; determining, by the one or more servers, whether a second portion of the real-time sensor data is outside of a second threshold value, the second threshold value being a static value; determining a second fault information in response to determining the second portion of the real-time sensor data is outside of the second threshold value; and displaying, in response to determining the second portion of the real-time sensor data is outside of the second threshold value, the second fault information on the graphical user interface, wherein determining both the first fault information and the second fault information comprises distinguishing between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

2. The method of claim 1, wherein determining the first fault information comprises distinguishing between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

3. A method for performing real-time pump monitoring with prescriptive analytics, the method comprising: receiving, by one or more servers, real-time sensor data from at least one sensor indicative of at least one characteristic of an operation of a pump of a pump system; updating, by the one or more servers, a first threshold value via use of machine learning to generate an updated first threshold value, the one or more servers being communicatively coupled to at least one of the at least one sensor; determining, by the one or more servers, whether a first portion of the real-time sensor data is outside of the updated first threshold value; determining a first fault information in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value; displaying, in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value, the first fault information on a graphical user interface of an administrative device; receiving, by the one or more servers, of a signal indicative of a modification, by a user, of a second threshold value, the modification of the second threshold value providing an updated second threshold value; comparing, by the one or more servers, a second portion of the real-time sensor data to the updated second threshold value; determining, by the one or more servers, a second fault information in response to determining the real-time sensor data is outside the updated second threshold value; and displaying, on the graphical user interface, the second fault information.

4. The method of claim 3, wherein the second portion of the real-time sensor data is different than the first portion of the real-time sensor data.

5. The method of claim 3, wherein the updated second threshold value is generated in response to a modification inputted by the user at the administrative device.

6. The method of claim 3, wherein determining the second fault information comprises distinguishing between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

7. A method for performing real-time pump monitoring with prescriptive analytics, the method comprising: receiving, by one or more servers, real-time sensor data from at least one sensor indicative of at least one characteristic of an operation of a pump of a pump system; updating, by the one or more servers, a first threshold value via use of machine learning to generate an updated first threshold value, the one or more servers being communicatively coupled to at least one of the at least one sensor; determining, by the one or more servers, whether a first portion of the real-time sensor data is outside of the updated first threshold value; determining a first fault information in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value; displaying, in response to determining the first portion of the real-time sensor data is outside of the updated first threshold value, the first fault information on a graphical user interface of an administrative device; comparing, by the one or more servers, a second portion of the real-time sensor data to a second threshold value, the second threshold value being based on a pump performance curve for the pump or a rotating apparatus characteristic curve; determining a second fault information in response to determining the real-time sensor data is outside the second threshold value; and displaying, on the graphical user interface, the second fault information.

8. The method of claim 7, wherein the second portion of the real-time sensor data is different than the first portion of the real-time sensor data.

9. The method of claim 7, wherein determining the second fault information comprises distinguishing between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

10. A system for real-time pump monitoring with prescriptive analytics, the system comprising: a pump of a pump control system; at least one sensor coupled to the pump and configured to generate real-time sensor data indicative of at least one characteristic of an operation of the pump; and at least one server communicatively coupled to the pump control system, each of the at least one server comprising a memory device coupled with at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to: receive the real-time sensor data; update a first threshold value via use of machine learning to generate an updated first threshold value; determine whether a first portion of the real-time sensor data is outside of the updated first threshold value; determine a first fault information in response to the first portion of the real-time sensor data being determined to be outside of the updated first threshold value; generate a first signal to facilitate a display of the first fault information on a graphical user interface of an administrative device; determine whether a second portion of the real-time sensor data is outside of a second threshold value, the second threshold value being a static value; determine a second fault information in response to the determination that the second portion of the real-time sensor data is outside of the second threshold value; generate a signal for a display, in response to the determination that the second portion of the real-time sensor data is outside of the second threshold value, of the second fault information on the graphical user interface, distinguish, for each the determination of the first fault information and the determination of the second fault information, between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

11. The system of claim 10, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to distinguish, for the determination of the first fault information, between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

12. A system for real-time pump monitoring with prescriptive analytics, the system comprising: a pump of a pump control system; at least one sensor coupled to the pump and configured to generate real-time sensor data indicative of at least one characteristic of an operation of the pump; and at least one server communicatively coupled to the pump control system, each of the at least one server comprising a memory device coupled with at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to: receive the real-time sensor data; update a first threshold value via use of machine learning to generate an updated first threshold value; determine whether a first portion of the real-time sensor data is outside of the updated first threshold value; determine a first fault information in response to the first portion of the real-time sensor data being determined to be outside of the updated first threshold value; generate a first signal to facilitate a display of the first fault information on a graphical user interface of an administrative device; receive a signal indicative of a modification, by a user, of a second threshold value, the modified second threshold value being an updated second threshold value; compare, a second portion of the real-time sensor data to the updated second threshold value; determine a second fault information in response to the determination of the real-time sensor data being outside the updated second threshold value; and generate a signal to facilitate a display, on the graphical user interface, of the second fault information.

13. The system of claim 12, wherein the second portion of the real-time sensor data is different than the first portion of the real-time sensor data.

14. The system of claim 12, wherein the updated second threshold value is generated in response to a modification inputted by the user via the administrative device.

15. The system of claim 12, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to distinguish, for the determination of the second fault information, between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.

16. A system for real-time pump monitoring with prescriptive analytics, the system comprising: a pump of a pump control system; at least one sensor coupled to the pump and configured to generate real-time sensor data indicative of at least one characteristic of an operation of the pump; and at least one server communicatively coupled to the pump control system, each of the at least one server comprising a memory device coupled with at least one processor, the memory device including instructions that when executed by the at least one processor cause the at least one processor to: receive the real-time sensor data; update a first threshold value via use of machine learning to generate an updated first threshold value; determine whether a first portion of the real-time sensor data is outside of the updated first threshold value; determine a first fault information in response to the first portion of the real-time sensor data being determined to be outside of the updated first threshold value; generate a first signal to facilitate a display of the first fault information on a graphical user interface of an administrative device; compare a second portion of the real-time sensor data to a second threshold value, the second threshold value being based on a pump performance curve for the pump or a rotating apparatus characteristic curve; determine a second fault information in response to the determination of the real-time sensor data being outside the second threshold value; and generate a signal to facilitate a display, on the graphical user interface, of the second fault information.

17. The system of claim 16, wherein the second portion of the real-time sensor data is different than the first portion of the real-time sensor data.

18. The system of claim 16, wherein the memory device further includes instructions that when executed by the at least one processor cause the at least one processor to distinguish, for the determination of the second fault information, between (1) a fault that requires an immediate forced shutdown to prevent damage to the pump and (2) a fault whose remediation can be delayed without damage to the pump.